Online Search For Fossett A Waste Of Time?

from the needle-in-a-haystack dept

Back in September, after millionaire Steve Fossett went missing in the Nevada backwoods, legions of web surfers enlisted to help in the search through Amazon's Mechanical Turk. The 50,000 volunteers looked through hundreds of thousands of satellite images of the area for any clues of Steve Fossett's plane. The whereabouts of Steve Fossett are still unknown, and now some are starting to question whether or not Mechanical Turk was a help or a hindrance during the search. Members of the search party, when fed search hints from the online volunteers, complained that the leads were false and ended up wasting their time. Sure, some poor leads may have been passed to search teams, but many important lessons were learned during this process that can be applied to future uses of this tool. So, hopefully search professionals will not be quick to attribute the outcome of the search to the use of Mechanical Turk -- after all, traditional methods to find Fossett were also unsuccessful. So, by understanding these tools better, a success surely lies in the future.

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Artificial Artificial Intelligence Tries To Track Down Steve Fossett

from the finding-a-needle-in-a-haystack dept

As the best thinkers are discussing the future of AI at the Singularity Summit, perhaps we shouldn't just be looking at ways to create better computer artificial intelligence, but at ways to more efficiently make use of human intelligence that's available all the time. For example, take a look at the technologies being used to harness human cognitive abilities to help in the search for Steve Fossett's plane in the vast desert of Nevada. Searchers are leveraging Amazon's Mechanical Turk community to quickly scan through Google Earth satellite imagery to flag areas where the plane might have crashed or eliminate barren areas where rescue pilots shouldn't focus on. At the time of this post, there are still over 100,000 blocks to be looked over with each block representing a 278x278 sq ft. area. At what appears to be a scanning rate of about 10-20 square grids/sec by the Turk community, the entire area of interest could theoretically be searched in less than 5 hours -- assuming that the system isn't showing the same photo to multiple people (as appears to be the case). Contrast that to the (super)computing resources required to process an equivalent image of more than 8 billion pixels (img dimension(256x256) x (numOfImgs)100k), on top of the difficult task of defining the object-of-interest to a computer (what does a plane wreck look like to a computer?).

In this instance, using simple coordination mechanisms, human intelligence becomes an economic way to solve a hard problem -- which is exactly the rationale behind Amazon's Mechanical Turk. We have seen projects using other hooks and mechanisms to leverage human intelligence, like Recaptcha for OCRing books, and the ESP game for tagging images -- and even the Techdirt Insight Community, which is bringing you this post. On a grander scale, Amazon's Mechanical Turk is trying to be a platform for "artificial artificial intelligence", though so far the success stories for MTurk have been minor. Even in this case, it's not entirely clear how useful it is (or how they got the latest satellite imagery ready to go for this task). In fact, while there are fairly stunning reports that, in searching for Fossett, the remains of eight other plane crashes have been discovered -- it doesn't sound like any of them were found via Mechanical Turk and Google Earth. Still, with all this talk about mashing up web services and better artificial intelligence, perhaps it's time we start thinking about more effective and efficient ways of leveraging human intelligence?

Teck Chia is an expert at the Insight Community. To get insight and analysis from Teck Chia and other experts on challenges your company faces, click here.

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